Present Value: David Easley on financial contagion and the effect of contradictory beliefs on market optimality

May 2, 2019

Contributing Authors: Caroline Wright and Michael Brady

Present Value, an independent editorial project produced and hosted by Johnson students, had the pleasure of interviewing David Easley, Henry Scarborough Professor of Social Science at Cornell University, about his incredibly popular Networks course, how financial market participants with different sets of beliefs can produce suboptimal market outcomes, and what it is like to work with one’s spouse.

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Networks: An interdisciplinary approach

Almost ten years ago, David Easley, along with computer scientist Jon Kleinberg, the Tisch University Professor of Computer Science at Cornell University, decided to do something new. After working together with other economists and computer scientists on concepts related to networks, they decided to create an introductory interdisciplinary course for undergraduates that never existed before on college campuses. The result is Networks, a course that explores “how the social, technological, and natural worlds are connected, and how the study of networks sheds light on these connections.” And, with 700 students enrolled each semester, it is the most popular course taught at Cornell.

The Networks course covers a lot of ground, including the dissemination of opinions, fads, and political movements through society and how Google uses auctions to conduct search results. “Google uses something called the generalized second price auction,” explains Easley, which is an auction format where the second highest bid wins. “At first glance, that seems really odd…[but] it’s been shown, actually quite a long time ago in economics, that in a second price auction, it’s actually a dominant strategy to bid truthfully.” By running this type of auction, Google ensures that bidders pay their true value for their placement in search results. “It’s a great example of a blend of computer science and economics, which is in part what I do,” says Easley. “There’s the computer science side about how to do search for Google and then how to make money from running really clever auctions…which comes from economics.”]

Contradictory beliefs and markets

Easley is currently examining how markets behave when different market participants have different goals. To explain this concept, Easley provides an example: You are the mayor of Ithaca and you are considering renovating the town commons. To determine whether or not you should do it, you survey the townspeople and find that everyone wants to move forward with the renovation. But when you start asking people why they want the renovation, their reasonings are thoroughly contradictory. For example, half of the people say they want the renovation because it will improve the life of the people of Ithaca, and they are not worried about it drawing tourists or causing congestion. The other half say that they don’t care about using the commons, but it will increase tourism, which will increase revenue and business for the city. Hence, since both scenarios will not come to fruition, either way, half of the people will eventually be upset. A decision with unanimous support that initially seemed like an obviously good decision, is no longer so because its supporters had different beliefs.

“It turns out that this is a really important phenomena,” explains Easley. “In financial markets, if people have different beliefs, it’s not clear how you should think about what’s an optimal decision. So, our usual results in economics that say, roughly, let people do whatever they want in terms of trading because that will produce optimal allocations actually don’t apply.” This predicament leads Easley to consider how we should think about regulating what people can do in markets. “In principle, regulations that people are opposed to are actually socially good…Here, for financial markets, our argument is not that the regulator knows what we should do, but he can say, ‘Look, I know I shouldn’t let you do what you want to do because it’s going to be socially bad.’”

Working with Maureen O’Hara

Easley has the pleasure of co-authoring several papers with his wife, Maureen O’Hara, who was also a guest on Present Value. “We started doing research together actually very early on and we’ve continued. We probably write an average of one paper together per year and we’ve done this for a lot of years now, so it’s a lot papers on a whole range of topics.” Recently, they published a paper about Bitcoin and even set up their own node. “We were interested in the question of whether the declining block reward that miners get was causing the increase in transaction fees in Bitcoin or whether the transaction fee increase in Bitcoin…was happening for other reasons.” Interestingly, Easley and O’Hara concluded that the declining block reward has nothing to do with the increase in transaction fees; it’s a completely separate phenomenon. “It’s natural to think that one caused the other because they happened at the same time. But, of course, the fact that they happen at the same time doesn’t mean that one causes the other.”

In addition to working with his wife, Easley routinely collaborates with other researchers in various departments across Cornell. “Working with co-authors is something I enjoy; it’s what I do all the time.” When asked what makes his working relationships successful, Easley gave this advice: “It’s important to treat your co-authors with respect and see what they have to say; try to see what you can get out of each other. With co-authors it’s really good to think about things from the perspective that people bring different skills and different insights.

About David Easley

David Easley is the Henry Scarborough Professor of Social Science at Cornell University. Easley holds a PhD in economics from Northwestern University, and is a fellow of the Econometric Society. His work focuses on economics, finance, and decision theory. In economics his work focuses on learning, wealth dynamics, and natural selection in markets. In finance, he focuses on market microstructure, which he studies alongside Maureen O’Hara. In decision theory, he focuses on modeling decision making in complex environments. He is the co-author of Networks, Crowds, and Markets: Reasoning about a Highly Connected World